%0 Journal Article
%T A CONTINUOUS TIME RECURRENT NEURAL NETWORK BASED METHOD TO SOLVE FUNCTIONAL MINIMIZATION PROBLEM<br>用连续回归神经网络求解泛函极值问题
%A Liu Heping
%A Zhang Lanling
%A Sun Yikang
%A <br>刘贺平
%A 张兰玲
%A 孙一康
%J 电子与信息学报
%D 2000
%I 
%X In this paper, the continuous time recurrent neural network is proposed to solve the functional minimization problem, which is often involved in estimation and control. At first, the continuous time BPTT algorithm corresponding to the problem is presented. Then,an on-line algorithm based on the amendments of the BPTT algorithm is discussed. This on-line algorithm paves the way for parallel realization.
%K Functional minimization
%K Continuous time recurrent neural network
%K BPTT algorithm
%K On-line learning algorithm<br>泛函极值
%K 连续回归神经网络
%K BPTT算法
%K 在线学习算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=83966C36ED3F20DF&yid=9806D0D4EAA9BED3&vid=BC12EA701C895178&iid=94C357A881DFC066&sid=B3AAD7DC3C912B50&eid=7F9B7E84827A650F&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=0&reference_num=8